{"id":"W2148558022","doi":"10.1109/mwscas.2007.4488742","title":"Design-specific supply and threshold voltage optimization in nanometer era","year":2007,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Low-power high-performance VLSI design","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cadence; Threshold voltage; Voltage; Computer science; Power–delay product; Leakage (economics); Power optimization; Dynamic voltage scaling; Power (physics); Very-large-scale integration; Nonlinear system; Electronic engineering; Optimal design; Energy (signal processing); Integrated circuit design; Efficient energy use; Mathematical optimization; Control theory (sociology); Electrical engineering; Transistor; Engineering; Mathematics; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003423746,0.0004175806,0.0003443179,0.0002216208,0.0001652429,0.0004093089,0.0003301493,0.0002944317,0.001512993],"category_scores_gemma":[0.0006279623,0.0002556257,0.0002356745,0.0003106351,0.0002756426,0.0005480178,0.0003313282,0.0003416151,0.000238236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005102762,"about_ca_system_score_gemma":0.0005719834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001108658,"about_ca_topic_score_gemma":0.002108575,"domain_scores_codex":[0.9998654,0.00004158533,0.000005421373,0.00001919992,0.00005404862,0.00001446461],"domain_scores_gemma":[0.9998448,0.00007118638,0.00002779398,0.0000212369,0.00003055609,0.000004489526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000298702,0.00001674631,0.0003251372,0.00009711166,0.00002000232,0.00003843975,0.00003562848,0.9183903,0.01934908,0.02066745,0.0006405081,0.04038979],"study_design_scores_gemma":[0.000007041388,0.00003033179,0.000178541,0.000008613912,0.000007661313,0.00002831168,0.00001126769,0.9799538,0.007483305,0.008735898,0.003549202,0.000006093284],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03074209,0.0008918113,0.9623044,0.0001664242,0.00001893856,0.000025323,0.0000632782,0.0002888065,0.005499029],"genre_scores_gemma":[0.5828624,0.0009544538,0.4104566,0.0001125309,0.00002424858,0.0001160012,0.0001187072,0.0001983762,0.005156619],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001512993,"threshold_uncertainty_score":0.005061507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01954620501254578,"score_gpt":0.204957039047041,"score_spread":0.1854108340344952,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}